2.4 Rail Transport
| Category ID | Description | EIC |
|---|---|---|
| 1681 | Locomotive Operations - Switching | 82082212100000 |
| 1722 | Locomotive Operations - Passenger | 82082612100000 |
| 2763 | Locomotive Operations - Line-Haul | 82082712100000 |
| 2764 | Locomotive Operations - Short Line | 82082312100000 |
| 2765 | Locomotive Operations - Industrial/Military | 82082812100000 |
Introduction
Locomotives play a vital role in California's transportation network, facilitating the movement of both freight and passengers. In California, locomotives are categorized into six types: Class I line haul, Class I switchers, short line, passenger, military, and industrial. Emissions from these categories are tracked under the following District categories: 1681 (Class I switchers), 1722 (passenger lines), 2763 (Class I line haul locomotives), 2764 (short line locomotives), and 2765 (military and industrial locomotives).
Class I line haul locomotives are used to transport freight by linking multiple locomotives in a series to push or pull a single line of railcars, both within and across the state. In the San Francisco Bay Area (SFBA), Union Pacific and BNSF Railways are the primary Class I operators. Most of their activity involves transporting goods and cargo to and from the Port of Oakland, the Port of Richmond, and other private terminals in the region. These locomotives are essential for moving cargo containers, bulk materials, vehicles, and chemical products from overseas and domestic sources to consumers and industries in the SFBA. Additionally, Class I line hauls support SFBA refineries by distributing and transporting refinery-related products. Class I switchers are smaller locomotives used in rail yards and are responsible for assembling and moving railcars destined for line haul locomotives. Passenger locomotives, such as those operated by Amtrak, provide transportation for travelers across the country or along commuter routes. Short line rail services are limited to specific businesses and operate within small geographic areas, such as the Richmond Pacific Railroad operating at the Levin Richmond Terminal. Military and industrial locomotives are used to transport equipment and goods within and around individual facilities. Once locomotives leave the SFBA, their emissions are no longer included in the region's inventory.
Most locomotives in these categories run exclusively on diesel fuel, which produces greenhouse gas (GHG) emissions during combustion. These emissions include carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O).
Methodology
CARB Sources
Categories 1681, 1722, 2763, 2764, and 2765 are area source locomotive categories where emissions are obtained from the California Air Resources Board (CARB), largely through the Off-Road Web Platform (2024, Off-Road Inventory version 1.0.7). This latest version of CARB’s inventory includes the addition of a new category to include emissions from industrial and military locomotives and changes to emissions based on the April 2023 adoption of the In-Use Locomotive Regulation for switchers, line haul, passenger, short line, and industrial locomotive engines (CARB, 2023).
The general methodology used by CARB to calculate emissions for the base year(s) of these area source locomotive categories are as follows:
Emissionsstate;national,pollutant = Activity Data × Emission Factorpollutant
Base Year(s) Emissions county,pollutant =
Emissionsstate;national,pollutant × Control Factorpollutant × Fractioncounty × GWPpollutant
Where:
- Base Year: is a year for which emissions data is directly reported by CARB and available.
- Activity Data: is the total statewide (or regional) throughput or activity data for applicable base year(s).
- Emissionsstate;national,pollutant: is the amount of emissions from a larger area (e.g. state or national level) to be allocated to a smaller regional area based on a proportional measure, such as allocating based on the ratio of county to state population.
- Emission Factorpollutant: is a factor that allocates an amount of emissions, in mass, of a particular pollutant by unit of activity data.
- Control Factorpollutant : is a fractional ratio (between 0 and 1) that captures the estimated reduction in emissions as a result of Air District rules and regulations.
- Fractioncounty : is the fraction of total regional emissions (between 0 and 1) estimated to be allocated to a particular county.
- GWPpollutant is the Global Warming Potential of a particular GHG pollutant. The current version of the GHG emissions inventory incorporates the global warming potential (GWP) reported in the Fifth Assessment report of the Intergovernmental Panel for Climate Change (IPCC, 2014). The GWPs for the three principal GHGs are 1 for carbon dioxide (CO2), 34 for methane (CH4), and 298 for nitrous oxide (N2O), when calculated on a 100-year basis with climate-carbon feedback included. The CARB emissions are given in MMTCO2eq using IPCC Assessment Report 4 (AR4; IPCC, 2007) and the Air District uses the values in IPCC Assessment Report 5 (AR5; IPCC, 2014). Since the GWPs for both species reported in this chapter, CO2 and N2O (including climate feedback), for both Assessment Reports, are the same, no correction is applied.
The development of these emissions inventories by CARB rely on the age of each locomotive, emission tier (i.e., emission standard the manufacturer was required to meet when making or rebuilding the locomotive engine), and activity data collected from the operators. Emissions are then estimated by using the emission factors by tier, multiplied by population and activity data expressed as fuel usage.
The CARB Off-Road locomotive inventory only includes base year 2022 county-level CO2 emissions for passenger, switcher, and short line locomotives. For these locomotive categories, CO2 emission rates are taken directly from the CARB Off-Road inventory to estimate GHG emissions. Since county-level CO2 emissions are not included for line haul and industrial/military locomotives, the Air District uses surrogate methods to estimate county-level GHG emissions for both categories based on available data. In addition, surrogate methods are used to estimate methane (CH4) and nitrous oxide (N2O) emissions for all locomotive categories. A detailed description on how surrogate method is used to populate CH4 and N2O emissions for locomotive categories is described in the next section.
Once base year emissions are determined, historical backcasting and forecasting of emissions relative to the base year emissions are estimated using growth profiles as follows:
Current Year Emissionscounty = Base Year(s) Emissioncounty x Growth Factor
Where:
- Growth Factor: is a scaling factor that is used to derive historical emissions estimates for years for which activity data and/or emissions are not available, and to forecast emissions for future years, using surrogates that are assumed to be representative of activity and/or emissions trends.
Forecasted future year populations are estimated by accounting for the rate at which older engines are retired or replaced, along with the overall population or activity growth needed to meet projected demands for goods.
Emissions Apportionment
Line Haul Locomotives
For line haul locomotives, District-level CO2 emissions are obtained from CARB’s Line Haul Locomotive Emission Inventory (CARB, 2021) and are apportioned to county-level emissions based on carbon monoxide (CO) emissions from the same data source. Criteria air pollutant emissions from the CARB Line Haul Locomotive Emission Inventory are the source for emissions included in the CARB Off-Road inventory. This approach uses CO emissions as a surrogate because CO and CO2 emission factors remain constant regardless of engine age or type (U.S. Department of Transportation, 2023). County-level CO emissions are used to derive county fractions which are used to apportion District-level CO2 emissions from the CARB Line Haul Locomotive Emission Inventory into county-level CO2 emissions.
Industrial/Military Locomotives
For industrial and military locomotives, CO2 emissions from the CARB Off-Road inventory are available at the statewide level, but not at the county level. Since activity data (horsepower-hours consumed) is available at both the statewide and county level, statewide emissions and activity are used to derive a statewide CO2 emission factor in units of tons per horsepower-hour consumed. This emission factor is multiplied by county-level activity data to estimate CO2 emissions for all Bay Area counties.
Since the CARB Off-Road inventory does not include CH4 or N2O emissions for any category, the CARB Statewide Greenhouse Gas Inventory Tool (CARB, 2023) is used to calculate representative CH4/CO2 and N2O /CO2 ratios for locomotives. These pollutant-to-pollutant ratios are applied to the CO2 emissions for all locomotive categories to derive county-level CH4 and N2O emissions. The only exception to this apportionment is CH4 emissions from line haul locomotives, where county-level emissions are available directly from the CARB Line Haul Locomotive Emission Inventory (CARB, 2021). The ratios are shown in the table below and are consistent across all locomotive categories.
Pollutant-to-Pollutant Ratio | Relative Emissions Value |
CH4/CO2 | 4.66 × 10-6 |
N2O/CO2 | 2.33 × 10-6 |
Once CH4 and N2O emissions are determined, the Global Warming Potential (GWP) of a particular GHG pollutant is used to derive emissions on a CO2-equivalent (CO2eq) basis. The current version of the GHG emissions inventory incorporates the GWPs reported in the Fifth Assessment report of the Intergovernmental Panel for Climate Change (IPCC, 2014). The GWPs for the three principal GHGs are 1 for carbon dioxide (CO2), 34 for methane (CH4), and 298 for nitrous oxide (N2O), when calculated on a 100-year basis with climate-carbon feedback included.
County Fractions
County fractions are presented in the following table and are based on CO2 emissions assigned to each county in the CARB Off-Road inventory for passenger, switcher, and short line locomotives. For industrial/military locomotives, country fractions are based on the activity in horsepower-hours assigned to each county in the CARB Off-Road inventory. For line haul locomotives, county fractions are based on CO emissions assigned to each county in the CARB Line Haul Locomotive Emission Inventory.
| ID | Description | ALA | CC | SF | SM | SNC | SOL |
|---|---|---|---|---|---|---|---|
| 1681 | Locomotive Operations - Switching | 0.30 | 0.43 | 0.06 | 0.00 | 0.00 | 0.21 |
| 1722 | Locomotive Operations - Passenger | 0.09 | 0.05 | 0.05 | 0.26 | 0.53 | 0.03 |
Emission Controls
Locomotives are federally regulated and are not subject to any additional rules adopted by the Air District. However, Union Pacific and BNSF entered into an agreement with CARB in 2005 to implement statewide diesel emissions reduction measures by reducing non-essential locomotive idling, installing idling emissions reduction devices, and maximizing the use of low sulfur fuel as locomotives enter the state. These voluntary actions lead to approximately 20% lower emissions in the SFBA from locomotive activities. In April 2023, CARB adopted the In-Use Locomotive Regulation requiring rail operators to limit idling to less than 30 minutes and frontload funds for future purchases of cleaner technologies and zero emissions locomotives. Reductions from these measures are incorporated in the latest CARB Off-Road inventory.
Historical Emissions
Historical GHG emissions are derived from the same source and methodology as base year emissions for each category. For passenger, switcher, short line, and industrial/military locomotives, historical emissions from 2000-2021 are derived from the CARB Off-Road inventory. For line haul locomotives, historical emissions from 2000-2021 are derived from CARB’s Line Haul Locomotive Emission Inventory.
Since CO2 emissions are not available from the CARB Off-Road inventory prior to 2020 for passenger, switcher, and short line locomotives and prior to 2011 for industrial/military locomotives, annual CO emissions are used to create a normalized backcast profile in place of CO2 emissions since CO and CO2 emission factors remain constant regardless of engine age or type (U.S. Department of Transportation, 2023).
Future Projections
Similar to historical emissions, future projections are also derived from the same source and methodology as base year emissions for each category. For passenger, switcher, short line, and industrial/military locomotives, projected emissions from 2023-2050 are derived from the CARB Off-Road inventory. For line haul locomotives, projected emissions from 2023-2050 are derived from CARB’s Line Haul Locomotive Emission Inventory. Projections incorporate the expected implementation of the In-Use Locomotive Regulation (CARB, 2022b), retirement of older engines and introduction of newer locomotives into the fleet, and activity growth needed to meet projected demands for goods.
Sample Calculation
Since the approach for apportioning GHG emissions differs between line haul and industrial/military locomotives, a sample calculation for Contra Costa County is presented for each in the tables below. Emissions for passenger, switcher, and short line locomotives are obtained directly from the CARB Off-Road inventory and emissions calculations follow similar methods outlined in the last six steps shown in the calculations below.
INDUSTRIAL/MILITARY LOCOMOTIVES | ||||
Step 1 | Obtain statewide CO2 emissions from | 24.3 | ||
Step 2 | Obtain statewide activity from | 12,934,842 | ||
Step 3 | Calculate CO2 emission factor | 24.3 tons/day ÷ 365 days/year = 6.86 × 10-4 tons/hp-hr | ||
Step 4 | Obtain Contra Costa county activity from CARB Off-Road inventory v1.0.7 | 580,683 | ||
Step 5 | Calculate Contra Costa County CO2 emissions (tons/year) | 6.86 × 10-4 tons/hp-hr × 580,683 hp-hr/year = 398.18 tons/year | ||
CO2 | CH4 | N2O | ||
Step 6 | Obtain statewide locomotive GHG emissions from CARB 2021 statewide GHG inventory (tons/day) | 3441 | 0.016 | 0.008 |
Step 7 | Derive ratio to CO2 emissions | 1 | 0.016 ÷ 3441 = 4.66 × 10-6 | 0.008 ÷ 3441 = 2.33 × 10-6 |
Step 8 | Calculate Contra Costa county GHG emissions (tons/year) | 398.18 | 4.66 × 10-6 × 398.18 = 0.0019 | 2.33 × 10-6 × 398.18 = 0.0009 |
Step 9 | Global Warming Potential | 1 | 34 | 298 |
Step 10 | Calculate emissions using GWP (tons CO2eq/year) | 398.18 = 398.18 | 0.0019 × 34 = 0.063 | 0.0009 × 298 = 0.28 |
398.18 + 0.063 + 0.28 = 398.52 tons CO2eq/year | ||||
Step 11 | Convert emissions to MTCO2eq/year | 398.52 tons CO2eq/year × 0.907 MT/tons = 361 MTCO2eq/year = 0.00036 MMTCO2eq/year | ||
LINE HAUL LOCOMOTIVES | |||||
Step 1 | Obtain district-wide CO2 emissions from CARB Line Haul Locomotive inventory (tons/day) | 129.76 | |||
Step 2 | Obtain Contra Costa county CO emissions CARB Line Haul Locomotive inventory (tons/day) | 0.235 | |||
Step 3 | Obtain district-wide CO emissions from CARB Line Haul Locomotive Inventory (tons/day) | 0.338 | |||
Step 4 | Determine county fraction for Contra Costa county | 0.235 ÷ 0.338 = 0.694 | |||
Step 5 | Apportion district-wide CO2 emissions to Contra Costa county (tons/day) | 129.76 × 0.694 = 90.04 | |||
Step 6 | Obtain Contra Costa county CH4 emissions from CARB Line Haul Locomotive inventory (tons/day) | 0.0040 | |||
CO2 | N2O | ||||
Step 7 | Obtain statewide Locomotive GHG emissions from CARB 2021 statewide GHG inventory (tons/day) | 3441 | 0.008 | ||
Step 8 | Derive ratio to CO2 Emissions | 1 | 0.008 ÷ 3441 = 2.33 × 10-6 | ||
CO2 | CH4 | N2O | |||
Step 9 | Calculate Contra Costa county GHG emissions (tons/day) | 90.04 | 0.0040 | 2.33 × 10-6 × 90.04 = 0.0002 | |
Step 10 | Global Warming Potential | 1 | 34 | 298 | |
Step 11 | Calculate emissions using GWP (tons CO2eq/year) | 90.04 = 398.18 | 0.0040 × 34 = 0.14 | 0.0002 × 298 = 0.063 | |
90.04 + 0.14 + 0.063 = 90.24 tons CO2eq/day | |||||
Step 12 | Convert emissions to MTCO2eq/year | 90.24 tons CO2eq/day × 365 day/year × 0.907 MT/tons = 29,880 MTCO2eq/year = 0.030 MMTCO2eq/year | |||
Assessment of Methodology
The methodology for estimating the emissions for locomotives remains consistent as it relies heavily on the inventory available from CARB. As each inventory is updated, the county fractions change depending on the activity level estimated for each county. The emission apportionment method relying on surrogate ratio constants remains consistent between GHG inventory years, although different compounds have been used to derive the surrogate ratios in past base year inventories. Most categories have transitioned away from the surrogate method as direct reported GHG emissions data has become available in the CARB Off-Road inventory.
Base Year | Revision | Reference |
2022 |
|
|
2015 |
|
|
2007 |
|
|
2002 |
|
|
Emissions
The table below shows the total greenhouse gas emissions by pollutant in metric tons of CO2 equivalents (MTCO2eq) for locomotives categories.
| ID | Description | CH4 | CO2 | N2O | Total |
|---|---|---|---|---|---|
| 1722 | Locomotive Operations - Passenger | 11.7 | 74125.3 | 51.4 | 74188.4 |
| 1681 | Locomotive Operations - Switching | 1.4 | 8622.3 | 6.1 | 8629.8 |
Summary of Base Year 2022 Emissions
A breakdown of the year 2022 locomotive GHG emissions contribution to the transportation sector and regional total is provided in the table below. The Air District anticipates greater reductions in future updates as CARB’s 2023 In-Use Locomotive Regulation are incorporated.
Contribution of Rail Transport Emissions by Sector| Subsector | Sector | Subsector GHG Emissions (MMTCO2eq) | Sector GHG Emissions (MMTCO2eq) | % of Sector |
|---|---|---|---|---|
| Rail Transport | Transportation | 0.08 | 22.60 | 0.37% |
Contribution of Rail Transport Emissions to Regional Total
| Subsector | Subsector GHG Emissions (MMTCO2eq) | Regional Total GHG Emissions (MMTCO2eq) | % of Regional Total |
|---|---|---|---|
| Rail Transport | 0.08 | 65.68 | 0.13% |
Trends
Locomotive emission trends from 1990 to 2050 are presented in the figure below.
Summary of Trends
Line haul locomotive emissions started to decline in 2005 after CARB and rail operators reached an agreement to install automatic idle-reduction technologies that turn off engines after 15 minutes of inactivity in all locomotives. The curtailment of locomotive idling resulted in less fuel usage and lower emissions in subsequent years once the controls were fully installed. Line haul locomotives are projected to see 1.45% growth per year from 2023 to 2050 due to growing demand, locally and nationally, for goods. The growth is expected to continue unless regulations are adopted to limit locomotive emissions. The In-Use Locomotive Regulation (CARB, 2023) is awaiting EPA approval before implementation begins. GHG emissions are expected to dramatically decline once EPA approves the regulation and operators are required to replace diesel locomotives with zero emission engines. Impacts to emissions from the recently adopted In-Use Locomotive Regulation (CARB, 2023) have been incorporated into future projections for passenger, short line, and switcher locomotives.
Uncertainties
The locomotive emissions inventory is based on reliable information including activity data, engine ages, and engine tiers provided to CARB by locomotive operators. The scaling of California-wide GHG to county level in the Bay Area for line haul and industrial/military locomotives introduces uncertainty to the estimates. However, much larger uncertainties are resolved by scaling the emissions by category, which accounts for different locomotive activities in each county. Forecasted emissions are heavily reliant on the assumption that EPA will approve the In-Use Locomotive regulation adopted by CARB, but these projections will change dramatically if the approval process is delayed or is denied.
Contact
Author: Tan Dinh
Reviewer: Virginia Lau / Abhinav Guha
Last Update: 08/28/2025
References
CARB. 2005. Air Resources Board and Railroad Statewide Agreement to Particulate Emissions Reduction Programs at California Rail Yards, California Air Resources Board. June 2005. Available at: https://ww2.arb.ca.gov/resources/documents/2005-statewide-railyard-agreement
CARB. 2021. Line-Haul Locomotive Emission Inventory. Appendix to the 2021 Line-Haul Locomotive Emission Inventory Report. Air Quality Planning and Science Division, Mobile Source Analysis Branch, California Air Resources Board. February 2021. Available at: https://ww2.arb.ca.gov/our-work/programs/msei/road-categories/road-diesel-models-and-documentation. Downloaded on 12/20/2024.
CARB. 2022a. 2022 Military and Industrial Locomotive Emission Inventory. Air Quality Planning and Science Division, Mobile Source Analysis Branch, California Air Resources Board. July 2022. Available at: https://ww2.arb.ca.gov/sites/default/files/2022-07/2022%20MI%20Locomotive%20Emission%20Inventory%20Document%2007112022%20ADA%20Checked.pdf
CARB. 2022b. CARB's 2022 In-Use Locomotive Emission Inventory (Appendix G): Regulation Proposal and Scenarios, California Air Resources Board. https://ww2.arb.ca.gov/sites/default/files/barcu/regact/2022/locomotive22/appg.pdf
CARB. 2023. Greenhouse Gas Emission Inventory, Query Tool for years 2000 to 2021 (2023 edition), California Air Resources Board. Available at: https://ww2.arb.ca.gov/applications/greenhouse-gas-emission-inventory-0.
CARB. 2024. Off-Road Web Platform version 1.0.7, California Air Resources Board. Available at: https://arb.ca.gov/emfac/offroad/
CARB. Downloaded on 12/20/2024.
IPCC. 2014. Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II, and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Core Writing Team, R.K. Pachauri and L.A. Meyers (eds.)]. IPCC, Geneva, Switzerland, 151 pp. Available here: https://www.ipcc.ch/site/assets/uploads/2018/02/SYR_AR5_FINAL_full.pdf
IPCC. 1995. IPCC Second Assessment Climate Change 1995, A Report of the Intergovernmental Panel on Climate Change. 63 pp. Available here: https://www.ipcc.ch/site/assets/uploads/2018/02/2nd-assessment-en_SYR.pdf
USDOT. 2023. FRA Locomotive Emissions Comparison Tool (LECT): Emissions Data Documentation, United States Department of Transportation. https://railroads.dot.gov/sites/fra.dot.gov/files/2023-12/Locomotive%20Emissions%20Comparison%20Tool_Emissions%20Data%20Documentation_FINAL_Dec2023_PDFa.pdf